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Record W6943889530 · doi:10.17605/osf.io/shfjg

Scoping review to assess the effectiveness of government-funded and population-based physical activity initiatives in Australia.

2023· other· en· W6943889530 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOpen Science Framework · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthGovernment (linguistics)Population healthHealth promotionPhysical activityAction planWelfareHealth policyAction (physics)

Abstract

fetched live from OpenAlex

The health benefits of physical activity play a vital public health role in the prevention and management of chronic disease and other health conditions (Halpin, Morales-Suárez-Varela & Martin-Moreno 2010; Thornton et al. 2016). Unfortunately, less than half of Australians are meeting the recommended physical activity level. (Australian Institute of Health and Welfare [AIHW] 2021). As such, there is a need for population-based approaches that can reach many Australians affordably and effectively. Government agencies commonly use evidence-based practice to improve public health outcomes (Titler 2008), and a scoping review will be conducted to examine government-funded population-based physical activity initiatives to understand their impacts, methods, gaps, and limitations. Moreover, we will gain extensive knowledge about the physical activity initiatives carried out in Australia and how they have been evaluated. Therefore, this scoping review will explore the effectiveness of government-funded population-based physical activity initiatives in Australia. References: Australian Institute of Health and Welfare (AIHW) 2021a, Australian Burden of Disease Study 2018: Interactive data on risk factor burden, viewed 03, June, 2022, https://www.aihw.gov.au/reports/burden-of-disease/abds-2018-interactive-data-risk-factors/contents/physical-inactivity Halpin, HA, Morales-Suárez-Varela, MM & Martin-Moreno, JM 2010, 'Chronic disease prevention and the new public health', Public Health Reviews, vol. 32, no. 1, pp. 120-154. DOI: 10.1007/BF03391595. SA Health 2022a, Wellbeing SA, viewed 08, August,2022, https://www.sahealth.sa.gov.au/wps/wcm/connect/public+content/sa+health+internet/about+us/wellbeing+sa/wellbeing+sa SA Health 2022b, The Physical Activity in Nature Action Plan 2021-2024, viewed 04,June,2022, https://www.sahealth.sa.gov.au/wps/wcm/connect/ South Australian Population Health Survey (SAPHS) 2019, Annual report 2020 - Adults, viewed 10 September 2022, https://das7nagdq54z0.cloudfront.net/downloads/SAPHS/SAPHS-2020-Annual-Report-Adults.pdf Thornton, JS, Frémont, P, Khan, K, Poirier, P, Fowles, J, Wells, GD & Frankovich, RJ 2016, 'Physical activity prescription: a critical opportunity to address a modifiable risk factor for the prevention and management of chronic disease: a position statement by the Canadian Academy of Sport and Exercise Medicine', British journal of sports medicine, vol. 50, no. 18, pp. 1109-1114. DOI: 10.1136/bjsports-2016-096291.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.121
GPT teacher head0.468
Teacher spread0.347 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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